CN116227087A - Method for predicting tensile characteristics of welded joint of thin-wall part based on finite element method - Google Patents
Method for predicting tensile characteristics of welded joint of thin-wall part based on finite element method Download PDFInfo
- Publication number
- CN116227087A CN116227087A CN202310316101.9A CN202310316101A CN116227087A CN 116227087 A CN116227087 A CN 116227087A CN 202310316101 A CN202310316101 A CN 202310316101A CN 116227087 A CN116227087 A CN 116227087A
- Authority
- CN
- China
- Prior art keywords
- model
- tensile
- welding
- finite element
- hardening
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 70
- 238000003466 welding Methods 0.000 claims abstract description 92
- 238000004088 simulation Methods 0.000 claims abstract description 57
- 238000009864 tensile test Methods 0.000 claims abstract description 42
- 238000004458 analytical method Methods 0.000 claims abstract description 24
- 230000008569 process Effects 0.000 claims abstract description 20
- 238000012360 testing method Methods 0.000 claims abstract description 20
- 230000008878 coupling Effects 0.000 claims abstract description 19
- 238000010168 coupling process Methods 0.000 claims abstract description 19
- 238000005859 coupling reaction Methods 0.000 claims abstract description 19
- 239000000463 material Substances 0.000 claims abstract description 19
- 238000011156 evaluation Methods 0.000 claims abstract description 7
- 230000014509 gene expression Effects 0.000 claims description 19
- 230000004323 axial length Effects 0.000 claims description 12
- 238000006073 displacement reaction Methods 0.000 claims description 9
- 238000009826 distribution Methods 0.000 claims description 6
- 238000005482 strain hardening Methods 0.000 claims description 6
- 238000002844 melting Methods 0.000 claims description 5
- 230000008018 melting Effects 0.000 claims description 5
- 230000004907 flux Effects 0.000 claims description 3
- 238000005520 cutting process Methods 0.000 claims 3
- 229910052751 metal Inorganic materials 0.000 description 4
- 239000002184 metal Substances 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 239000007769 metal material Substances 0.000 description 3
- 229910000838 Al alloy Inorganic materials 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000005094 computer simulation Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 229910052782 aluminium Inorganic materials 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000011089 mechanical engineering Methods 0.000 description 1
- 238000005272 metallurgy Methods 0.000 description 1
- 150000002739 metals Chemical class 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Geometry (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The invention discloses a method for predicting the tensile characteristics of a welding joint of a thin-wall part based on a finite element method, which comprises the steps of carrying out welding thermal coupling analysis by changing welding process parameters and establishing a first finite element model corresponding to a welding test; preparing a tensile sample, carrying out a tensile test, fitting a hardening model based on test data, and constructing a linear combination hardening model of the hardening model so as to improve prediction accuracy; establishing a second finite element model corresponding to the tensile test, and applying the hardening model to the second finite element model; combining a tensile test and a tensile simulation result to obtain the relation between the breaking strain and the stress triaxial degree of the material, and then fitting a breaking failure model; the hardening model, the combined hardening model and the fracture failure model are combined, and the prediction precision of the combined use of different hardening models and failure models is compared by adopting an evaluation function, so that the aims of predicting the tensile characteristics and the fracture behavior of the welded joint are finally achieved, and a basis is provided for predicting the damage fracture failure of the welded structure in the service process of the welded joint.
Description
Technical Field
The invention belongs to the field of mechanical engineering and welding processing application, and particularly relates to a method for predicting the tensile characteristics of a welding joint of a thin-wall part based on a finite element method.
Background
The welding is a common connecting process for thin-wall parts, and is a manufacturing process and technology for connecting metals in a heating, high-temperature or high-pressure mode, wherein arc welding is widely applied to the fields of automobiles, airplanes, radar antennas and ships, but the problems that safety and fracture failure are difficult to predict due to the fact that physical, heat transfer, metallurgy, mechanics and the like are involved in the welding process are solved, and the safety of a welded joint is difficult to evaluate in service.
The mechanical property test of the metal material is simulated and analyzed by utilizing finite element modeling software, so that the stress-strain state of the metal material in the whole test process can be intuitively analyzed, the stress-strain change of the metal material can be effectively predicted, the failure analysis of the metal component in the service process can be realized, the structure of the metal component can be optimized, and guidance and basis can be provided for the metal manufacturing process. CN111523183 discloses a "simulation modeling method for mechanical properties and fracture failure of welded joint", the invention uses finite element modeling analysis method to obtain mechanical properties of welded joint, in the course of which the influence of temperature on different regions of the joint is considered, and different material constitutive parameters are given to the regions, so as to implement accurate description of mechanical properties of microscopic regions of welded joint, but the constitutive model applied in the finite element model is single, and the method still has optimized space.
In conclusion, the fracture failure behavior and the mechanical property of the welding joint are accurately predicted, and the method has great significance in optimizing welding process parameters and evaluating the safety of the welding joint.
Disclosure of Invention
The invention aims at solving the technical problems of the prior art, and provides a method for predicting the tensile characteristics of a welding joint of a thin-wall part based on a finite element method.
The technical scheme for realizing the invention is as follows: a method for predicting the tensile characteristics of a welded joint of a thin-wall part based on a finite element method comprises the following steps:
step 1: and (3) carrying out grouping welding tests by changing welding process parameters, preparing a welding joint, and recording the welding process parameters and the size of a welding piece.
Step 2: and (3) establishing a first finite element model corresponding to the welding test working condition in the step (1), and completing welding thermal coupling analysis to obtain a thermal coupling analysis result.
Step 3: preparing a tensile sample:
the welded joint was cut into tensile test pieces for tensile test, and then tensile test was performed, and load displacement data of the tensile test pieces in the tensile test were recorded.
Step 4: according to load displacement data of a tensile sample, acquiring a real stress-strain relation of the material, fitting a hardening model and a combined hardening model, combining a thermal coupling analysis result, establishing a second finite element model corresponding to a tensile test, and applying the hardening model to the second finite element model to perform tensile simulation to obtain a first tensile simulation result.
Step 5: based on the real stress-strain relation of the material and the first tensile simulation result, the triaxial relation of the fracture strain and stress of the material is obtained, and then a fracture failure model is fitted.
Step 6: and applying the hardening model and the fracture failure model to a second finite element model in a combined way to perform stretching simulation, so as to obtain a second stretching simulation result. And applying the combined hardening model and the fracture failure model to the second finite element model in a combined way to perform stretching simulation, so as to obtain a third stretching simulation result.
Step 7: and evaluating the second stretching simulation result and the third stretching simulation result through an evaluation function, and comparing the prediction precision of the combined use of different hardening models and fracture failure models.
Compared with the prior art, the invention has the following beneficial effects:
(1) According to the invention, a thermodynamic coupling analysis result is used in the finite element stretching simulation, so that the consistency of the model in the finite element analysis is achieved.
(2) The invention realizes the joint utilization of the hardening model and the fracture failure model, and provides basis for the prediction of the damage fracture failure of the welding structure and the improvement of the welding performance in the service process of the welding joint.
(3) The invention replaces a large number of tests by finite element simulation, and effectively reduces the cost.
Drawings
FIG. 1 is a schematic diagram of weld joint dimensions and boundary conditions in an embodiment of the present invention.
Fig. 2 is a diagram of a first finite element model in an embodiment of the present invention.
FIG. 3 is a flow chart of modeling analysis of thermal coupling and stretch simulation in an embodiment of the present invention.
Fig. 4 is a diagram of a second finite element model in an embodiment of the present invention.
FIG. 5 is a graph showing the results of the second and third tensile simulations and the actual stress-strain curves of the test in the embodiment of the present invention.
FIG. 6 is a graph showing the trend of the yield strength and the tensile strength in the second and third finite element simulation results and the tensile test results at different currents in the examples of the present invention.
FIG. 7 is a graph showing the yield strength relative error, the tensile strength relative error, the correlation coefficient and the mean square error of the second and third finite element simulation results at different currents in the embodiment of the present invention.
Fig. 8 is a flowchart of a method for predicting the tensile characteristics of a welded joint of a thin-walled workpiece based on a finite element method.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by one of ordinary skill in the art without creative efforts, are within the scope of the present invention based on the embodiments of the present invention.
In addition, the technical solutions of the embodiments of the present invention may be combined with each other, but it is necessary to base that the technical solutions can be implemented by those skilled in the art, and when the technical solutions are contradictory or cannot be implemented, the combination of the technical solutions should be considered to be absent, and not included in the scope of protection claimed in the present invention.
The following describes the specific embodiments, technical difficulties and inventions of the present invention in further detail in connection with the present design examples.
Referring to fig. 8, the method for predicting the tensile characteristics of the welded joint of the thin-wall part based on the finite element method comprises the following steps:
step 1: and (3) carrying out grouping welding tests by changing welding process parameters, preparing a welding joint, and recording the welding process parameters and the size of a welding piece. The welding technological parameters include welding current, welding voltage and welding speed, and the welding part size includes plate thickness, plate height, plate width and welding seam cross-section shape.
Step 2: and (3) establishing a first finite element model corresponding to the welding test working condition in the step (1), and adopting a double-ellipsoid heat source model as a heat source to finish welding thermal coupling analysis to obtain a thermal coupling analysis result.
The double ellipsoid heat source model expression is as follows:
f 1 +f 2 ＝2
wherein q 1 Represents the heat flow density of the front semi-ellipsoid, q 2 Representing the heat flux density of the rear semi-ellipsoidX represents the distance in the welding direction from the heat source center, y represents the distance in the melting width direction from the heat source center, z represents the distance in the melting depth direction from the heat source center, a 1 Represents the front half axial length of the welding direction, a 2 The rear half axial length in the welding direction is represented, b represents the half axial length in the welding line width direction, c represents the half axial length in the welding line depth direction, f 1 Representing the energy distribution coefficient of the front semi-ellipsoid, f 2 The energy distribution coefficient of the rear semi-ellipsoid is represented, η represents the thermal efficiency, I represents the welding current, and U represents the welding voltage.
Step 3: preparing a tensile sample:
the welded joint was cut into tensile test pieces for tensile test, and then tensile test was performed, and load displacement data of the tensile test pieces in the tensile test were recorded.
Step 4: and acquiring the real stress-strain relation of the material according to the load displacement data of the tensile sample, and then fitting the hardening model and the combined hardening model. Dividing the geometric model in the thermal coupling analysis result in the step 2 according to the size of a tensile sample in three-dimensional software, establishing a second finite element model corresponding to a tensile test, and applying a hardening model to the second finite element model to perform tensile simulation to obtain a first tensile simulation result, wherein the method comprises the following steps of:
the hardening models include a Johnson-Cook hardening model, a Swift model, a Voce model, and an H-S model;
the Johnson-Cook hardening model expression is as follows:
wherein, sigma is the equivalent stress,
is equivalent to plastic strain>
Is equivalent plastic strain rate, +.>
To reference the equivalent plastic strain rate, T is the current temperature, T r For reference temperature, T m A, B, C, n, m, which is the melting point temperature, represents the initial yield stress, the strain hardening coefficient, the strain rate coefficient, the strain hardening index, the heat softening index, respectively, at the reference temperature.
The expression of the adopted Swift model, voce model and H-S model are respectively as follows:
wherein, sigma is the equivalent stress,
for equivalent plastic strain, sigma s Indicating yield stress, ε s Representing yield strain, phi and xi each represent parameters determined by fitting, and r, t, u and v each represent hardening coefficients.
The combined hardening model comprises a swift+Voce model, an H-S+Voce model and a swift+H-S model, and the expressions are as follows:
where λ is a weighting factor ranging from 0 to 1.
Step 5: based on the real stress-strain relation of the material and the first tensile simulation result, the triaxial relation of the fracture strain and stress of the material is obtained, and then a fracture failure model is fitted. The method comprises the following steps:
calculating the breaking strain value epsilon of a welded joint in a tensile test f Deriving stress triaxial degree of the weld joint in the first tensile simulation result, and taking stress triaxial degree sigma of the tensile sample at the moment of fracture in the tensile test * And obtaining the triaxial relation between the fracture strain and the stress of the material, and fitting a fracture failure model.
The fracture failure model adopts a Johnson-Cook fracture failure model, and the expression epsilon of the model is f The following are provided:
wherein D is 1 ,D 2 And D 3 Is a model parameter.
Step 6: applying the hardening model and the fracture failure model to a second finite element model in a combined way to perform stretching simulation to obtain a second stretching simulation result; and applying the combined hardening model and the fracture failure model to the second finite element model in a combined way to perform stretching simulation, so as to obtain a third stretching simulation result.
Step 7: and evaluating the second tensile simulation result and the third tensile simulation result by adopting the correlation coefficient R and the mean square error MSE as evaluation functions, and comparing the prediction precision of the combined use of different hardening models and fracture failure models.
The correlation coefficient R and the mean square error MSE expression are respectively as follows:
where N is the total number of data, i is the data sequence number,
is the true stress in tensile test, +.>
Is the average stress in tensile test, +.>
Is the true stress in the tensile finite element simulation, < ->
Is the average stress in the tensile finite element simulation. />
Example 1
Taking an aluminum alloy plate T-shaped welding joint as an example, under the condition of certain welding voltage and welding speed, adjusting welding current and changing heat input, the invention provides a method for predicting the tensile characteristics of a welding joint of a thin-wall part based on a finite element method, which comprises the following steps:
step 1: and (3) carrying out grouping welding tests by changing welding process parameters, preparing a welding joint, and recording the welding process parameters and the size of a welding piece.
Wherein, a welded joint was prepared, as shown in FIG. 1, the plate thickness H of the aluminum alloy plate was 2mm, and the bottom plate size was L 1 ×L 2 Web dimensions L =300 mm×100mm 3 ×L 4 =100 mm×100mm. Four different groups of welding currents are selected for grouping welding tests.
Step 2: and (3) establishing a first finite element model corresponding to the welding test working condition in the step (1), and completing welding thermal coupling analysis to obtain a thermal coupling analysis result.
The geometric model of the welded joint is built according to the actual size of the aluminum plate, three-dimensional 8-node units are adopted for grid division, transition grid division is adopted, time cost and simulation precision can be considered, and the minimum size of a welding seam grid is 1mm multiplied by 1mm as shown in fig. 2.
Wherein the circled area node of fig. 1 is fixed in the first finite element model to correspond to the process of spot welding in the welding. The heat source in the thermodynamic coupling analysis adopts a double-ellipsoid heat source model, and is realized in finite element software by writing a Dflux subprogram. The double ellipsoid heat source model expression is as follows:
f 1 +f 2 ＝2
wherein q 1 Represents the heat flow density of the front semi-ellipsoid, q 2 The heat flux density of the rear half ellipsoid is expressed, x is the distance from the center of the heat source in the welding direction, y is the distance from the center of the heat source in the width direction, z is the distance from the center of the heat source in the depth direction, a 1 Represents the front half axial length of the welding direction, a 2 The rear half axial length in the welding direction is represented, b represents the half axial length in the welding line width direction, c represents the half axial length in the welding line depth direction, f 1 Representing the energy distribution coefficient of the front semi-ellipsoid, f 2 The energy distribution coefficient of the rear semi-ellipsoid is represented, η represents the thermal efficiency, I represents the welding current, and U represents the welding voltage.
Wherein the first finite element model modeling analysis process is shown in fig. 3 (1).
Step 3: preparing a tensile sample:
the welded joint is cut into a tensile sample for tensile test, then the tensile test is carried out, the tensile test is carried out on the welded joint under different welding currents by taking the tensile sample (2) in fig. 1, the tensile test is carried out on a universal testing machine, the tensile speed is set, and the load displacement data of the tensile sample in the tensile test are recorded.
Step 4: according to load displacement data of a tensile sample, acquiring a real stress-strain relation of the material, fitting a hardening model and a combined hardening model, combining a thermal coupling analysis result, establishing a second finite element model corresponding to a tensile test, and applying the hardening model to the second finite element model to perform tensile simulation to obtain a first tensile simulation result.
The load displacement data of the tensile sample is processed according to the following expression to obtain a real stress-strain relation.
Wherein: epsilon t Representing true strain, sigma t Representing true stress, L 0 Representing the original length of the gauge length segment, L representing the length in the stretch of the gauge length segment, F representing the load, A 0 Gauge length section cross-sectional area.
The hardening model comprises a Johnson-Cook hardening model, a Swift model, a Voce model and an H-S model.
The Johnson-Cook hardening model expression is as follows:
wherein, sigma is the equivalent stress,
is equivalent to plastic strain>
Is equivalent plastic strain rate, +.>
To reference the equivalent plastic strain rate, T is the current temperature, T r For reference temperature, T m A, B, C, n, m, which is the melting point temperature, represents the initial yield stress, the strain hardening coefficient, the strain rate coefficient, the strain hardening index, the heat softening index, respectively, at the reference temperature.
In this example, the deformation temperature rise is ignored, the tensile sample temperature is equal to room temperature, and the strain rate is the same as the quasi-static reference strain rate, so the Johnson-Cook model is simplified to:
the expression of the adopted Swift model, voce model and H-S model are respectively as follows:
wherein, sigma is the equivalent stress,
for equivalent plastic strain, sigma s Indicating yield stress, ε s Representing yield strain, phi and xi each represent parameters determined by fitting, and r, t, u and v each represent hardening coefficients.
The combined hardening model comprises a swift+Voce model, an H-S+Voce model and a swift+H-S model, and the expressions are as follows:
the coefficient λ is a weighting factor ranging from 0 to 1, and λ= 0.2,0.4,0.6,0.8 in this embodiment.
The specific process of establishing the second finite element model is as follows:
and (3) dividing the geometric model of the thermal coupling analysis result in the step (2) according to the size of a tensile sample in a tensile test, and restricting all degrees of freedom of a fixed end as shown in fig. 4, wherein a three-dimensional 8-node unit is adopted as a model grid.
The second finite element model tensile simulation modeling analysis flow is shown in (2) in fig. 3.
Step 5: based on the real stress-strain relation of the material and the first tensile simulation result, the triaxial relation of the fracture strain and stress of the material is obtained, and then a fracture failure model is fitted, wherein the fracture failure model is specifically as follows:
calculating the breaking strain value epsilon of a welded joint in a tensile test f Deriving stress triaxial degree at the weld joint in the first tensile simulation result, and taking stress triaxial degree sigma at the moment when the tensile sample breaks in the tensile test * And obtaining the triaxial relation between the fracture strain and the stress of the material, and fitting a fracture failure model.
Wherein the fracture failure model adopts a Johnson-Cook fracture failure model, and the expression epsilon thereof f The following are provided:
wherein D is 1 ,D 2 And D 3 Is a model parameter.
Step 6: the combined application of the hardening model and the fracture failure model in the second finite element model is performed with the written VUMAT+VUSDFLD subroutine to obtain a second tensile simulation result; and applying the combined hardening model and the fracture failure model to the second finite element model in a combined way to perform stretching simulation, so as to obtain a third stretching simulation result.
The actual stress-strain curves in the second and third finite element tensile simulation results are shown in fig. 5, and the yield strength and tensile strength change trend curves in the second and third finite element simulation results and the tensile test results under different currents are shown in fig. 6.
Fig. 5 shows that the true stress-strain curve is affected by the hardening model and the combined hardening model, and that the true stress-strain curve simulated by the different hardening models is similar to the results obtained by the test, in particular the linear phase and the hardening phase. The initial fracture strain of the test is 0.156324, the initial fracture strain of the H-S model and the combined Swift+Voce model is 0.157302,0.155062, the relative error of the lambda=0.8 is less than 1%, and the maximum relative error of the lambda=0.2 is about 6% for the H-S+Voce model.
FIG. 6 shows that the yield strength of the Swift model is better than the other hardening models in terms of yield strength, and that the relative errors in yield strength of the H-S, J-C (Johnson-Cook), swift and Voce models are 10.1%, 12.6, 4.0% and 9.9%, respectively, for example, I=100deg.A; the combined hardening model is better matched with the test value compared with the hardening model, and takes I=170A as an example, the relative error of the J-C model is up to 13.4% except that the relative error of the Voce model is lower in the hardening model, and the relative error of the combined hardening model is lower than 4%, wherein the relative error of the Swift+Voce combined hardening model is 2.3% at lambda=0.8. In terms of tensile strength, the simulation results of the hardening model and the combined hardening model have smaller difference in the degree of coincidence with the test, and the relative errors of the H-S, J-C, swift and the Voce model are respectively 0.47%, 0.05%, 0.20% and 0.99% by taking I=220A as an example, and the relative errors of the combined hardening model are also below 1%;
step 7: and evaluating the second stretching simulation result and the third stretching simulation result through an evaluation function, and comparing the prediction precision of the combined use of different hardening models and fracture failure models. The yield strength relative error, tensile strength relative error, correlation coefficient and mean square error of the second and third finite element simulation results at different currents are shown in fig. 7.
Wherein, the evaluation function adopts a correlation coefficient R and a mean square error MSE, and the expression is as follows:
where N is the total number of data, i is the data sequence number,
is the true stress in tensile test, +.>
Is the average stress in tensile test, +.>
Is the true stress in the tensile finite element simulation, < ->
Is the average stress in the tensile finite element simulation.
FIG. 7 shows that the mean relative error of the Swift model for the tensile properties of the four sets of tensile samples was below 6%, with the mean relative error for the tensile strength predictions reaching 2.35%; when λ=0.2, the correlation coefficient cmax is 0.99702 in the swift+h-S model; h-s+voce at λ=0.2, the Mean Square Error (MSE) is only 0.13542 at minimum.
The results prove that the stress-strain results obtained by the models are better in consistency with tensile test results, have higher prediction precision, can provide basis for the prediction of the damage fracture failure of the welding structure and the improvement of the welding performance in the service process of the welding joint, and are expected to provide a better hardening model by different comparison of different hardening models.
Claims (10)
1. A method for predicting the tensile characteristics of a welded joint of a thin-wall part based on a finite element method is characterized by comprising the following steps:
step 1: performing grouping welding tests by changing welding process parameters, preparing a welding joint, and recording the welding process parameters and the size of a welding piece;
step 2: establishing a first finite element model corresponding to the welding test working condition in the step 1, and completing welding thermal coupling analysis to obtain a thermal coupling analysis result;
step 3: preparing a tensile sample:
cutting the welded joint into a tensile sample for a tensile test, then carrying out the tensile test, and recording load displacement data of the tensile sample in the tensile test;
step 4: according to load displacement data of a tensile sample, acquiring a real stress-strain relation of the material, fitting a hardening model and a combined hardening model, combining a thermal coupling analysis result, establishing a second finite element model corresponding to a tensile test, and applying the hardening model to the second finite element model to perform tensile simulation to obtain a first tensile simulation result;
step 5: based on the real stress-strain relation of the material and the first tensile simulation result, acquiring the triaxial relation of the fracture strain and stress of the material, and fitting a fracture failure model;
step 6: applying the hardening model and the fracture failure model to a second finite element model in a combined way to perform stretching simulation to obtain a second stretching simulation result; applying the combined hardening model and the fracture failure model to the second finite element model in a combined way to perform stretching simulation to obtain a third stretching simulation result;
step 7: and evaluating the second stretching simulation result and the third stretching simulation result through an evaluation function, and comparing the prediction precision of the combined use of different hardening models and fracture failure models.
2. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in the step 1, welding technological parameters include welding current, welding voltage and welding speed, and the sizes of welding parts include plate thickness, plate height, plate width and the size of the section shape of a welding seam.
3. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in the step 2, during thermal coupling analysis, a double-ellipsoid heat source model is adopted as a heat source, and the expression of the double-ellipsoid heat source model is as follows:
f 1 +f 2 ＝2
wherein q 1 Represents the heat flow density of the front semi-ellipsoid, q 2 The heat flux density of the rear half ellipsoid is expressed, x is the distance from the center of the heat source in the welding direction, y is the distance from the center of the heat source in the width direction, z is the distance from the center of the heat source in the depth direction, a 1 Represents the front half axial length of the welding direction, a 2 The rear half axial length in the welding direction is represented, b represents the half axial length in the welding line width direction, c represents the half axial length in the welding line depth direction, f 1 Representing the energy distribution coefficient of the front semi-ellipsoid, f 2 The energy distribution coefficient of the rear semi-ellipsoid is represented, η represents the thermal efficiency, I represents the welding current, and U represents the welding voltage.
4. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in the step 3, the cutting mode of the welding joint is wire cutting.
5. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in step 4, the hardening model comprises a Johnson-Cook hardening model, a Swift model, a Voce model and an H-S model;
the Johnson-Cook hardening model expression is as follows:
wherein, sigma is the equivalent stress,
is equivalent to plastic strain>
Is equivalent plastic strain rate, +.>
To reference the equivalent plastic strain rate, T is the current temperature, T r For reference temperature, T m A, B, C, n, m, which is the melting point temperature, respectively represents the initial yield stress, the strain hardening coefficient, the strain rate coefficient, the strain hardening index, and the heat softening index at the reference temperature;
the adopted Swift model, voce model and H-S model expression are respectively represented as follows:
wherein, sigma is the equivalent stress,
for equivalent plastic strain, sigma s Indicating yield stress, ε s Representing yield strain, phi and xi each represent parameters determined by fitting, and r, t, u and v each represent hardening coefficients.
6. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 5, wherein the method comprises the steps of: in step 4, the combined hardening model includes a shift+Voce model, an H-S+Voce model, and a shift+H-S model, the expressions of which are as follows, respectively:
where λ is a weighting factor ranging from 0 to 1.
7. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in step 4, the geometric model in the thermal coupling analysis result in step 2 is divided according to the size of the tensile sample in three-dimensional software, and a second finite element model corresponding to the tensile test is established.
8. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in step 5, based on the real stress-strain relation of the material and the first tensile simulation result, the relation between the breaking strain of the material and the triaxial degree of stress is obtained, and then a breaking failure model is fitted, specifically as follows:
calculating the breaking strain value epsilon of a welded joint in a tensile test f Deriving stress triaxial degree at the weld joint in the first tensile simulation result, and taking stress triaxial degree sigma at the moment when the tensile sample breaks in the tensile test * And obtaining the triaxial relation between the fracture strain and the stress of the material, and fitting a fracture failure model.
9. Finite element based according to claim 8The method for predicting the tensile characteristics of the welded joint of the thin-wall part is characterized by comprising the following steps of: in step 5, the fracture failure model adopts a Johnson-Cook fracture failure model, the expression epsilon of which is f The following are provided:
wherein D is 1 ,D 2 And D 3 Is a model parameter.
10. The method for predicting the tensile characteristics of a welded joint of thin-walled workpieces based on the finite element method according to claim 1, wherein the method comprises the steps of: in step 7, the evaluation function uses the correlation coefficient R and the mean square error MSE, and the expression is as follows:
where N is the total number of data, i is the data sequence number,
is the true stress in tensile test, +.>
Is the average stress in tensile test, +.>
Is the true stress in the tensile finite element simulation, < ->
Is the average stress in the tensile finite element simulation. />
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310316101.9A CN116227087A (en) | 2023-03-29 | 2023-03-29 | Method for predicting tensile characteristics of welded joint of thin-wall part based on finite element method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310316101.9A CN116227087A (en) | 2023-03-29 | 2023-03-29 | Method for predicting tensile characteristics of welded joint of thin-wall part based on finite element method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116227087A true CN116227087A (en) | 2023-06-06 |
Family
ID=86575175
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310316101.9A Pending CN116227087A (en) | 2023-03-29 | 2023-03-29 | Method for predicting tensile characteristics of welded joint of thin-wall part based on finite element method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116227087A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117542945A (en) * | 2023-11-13 | 2024-02-09 | 迈铼德微电子科技(无锡)有限公司 | Bonding method of flip MICRO LED chip and substrate |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160084802A1 (en) * | 2014-09-19 | 2016-03-24 | King Fahd University Of Petroleum And Minerals | Process for determining weld quality using flexural characteristics |
| CN108022014A (en) * | 2017-12-05 | 2018-05-11 | 国网山东省电力公司济南供电公司 | A kind of Load Prediction In Power Systems method and system |
| CN111523183A (en) * | 2020-04-20 | 2020-08-11 | 湖南大学 | Simulation modeling method for mechanical property and fracture failure of welding joint |
| US20200347472A1 (en) * | 2019-04-30 | 2020-11-05 | North Carolina State University | Ductile Fuse for Special Concentrically Braced Frames and Related Methods |
| CN113139347A (en) * | 2021-05-10 | 2021-07-20 | 中南林业科技大学 | Forest land drought risk early warning method |
| CN113281671A (en) * | 2021-06-28 | 2021-08-20 | 长安大学 | Lithium ion battery remaining service life prediction method and system based on IGS-SVM |
| CN114201897A (en) * | 2021-12-06 | 2022-03-18 | 上海交通大学 | Metal sheet edge cracking prediction considering blanking history |
| CN114528739A (en) * | 2022-02-28 | 2022-05-24 | 重庆长安汽车股份有限公司 | Simulation method for automobile hub fracture failure |
-
2023
- 2023-03-29 CN CN202310316101.9A patent/CN116227087A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160084802A1 (en) * | 2014-09-19 | 2016-03-24 | King Fahd University Of Petroleum And Minerals | Process for determining weld quality using flexural characteristics |
| CN108022014A (en) * | 2017-12-05 | 2018-05-11 | 国网山东省电力公司济南供电公司 | A kind of Load Prediction In Power Systems method and system |
| US20200347472A1 (en) * | 2019-04-30 | 2020-11-05 | North Carolina State University | Ductile Fuse for Special Concentrically Braced Frames and Related Methods |
| CN111523183A (en) * | 2020-04-20 | 2020-08-11 | 湖南大学 | Simulation modeling method for mechanical property and fracture failure of welding joint |
| CN113139347A (en) * | 2021-05-10 | 2021-07-20 | 中南林业科技大学 | Forest land drought risk early warning method |
| CN113281671A (en) * | 2021-06-28 | 2021-08-20 | 长安大学 | Lithium ion battery remaining service life prediction method and system based on IGS-SVM |
| CN114201897A (en) * | 2021-12-06 | 2022-03-18 | 上海交通大学 | Metal sheet edge cracking prediction considering blanking history |
| CN114528739A (en) * | 2022-02-28 | 2022-05-24 | 重庆长安汽车股份有限公司 | Simulation method for automobile hub fracture failure |
Non-Patent Citations (1)
| Title |
|---|
| 徐从昌: "热处理和焊接对车用6系铝合金组织性能及服役失效行为的影响", 《中国博士学位论文全文数据库》, pages 28 - 73 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117542945A (en) * | 2023-11-13 | 2024-02-09 | 迈铼德微电子科技(无锡)有限公司 | Bonding method of flip MICRO LED chip and substrate |
| CN117542945B (en) * | 2023-11-13 | 2024-05-14 | 迈铼德微电子科技(无锡)有限公司 | Bonding method of flip MICRO LED chip and substrate |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Govik et al. | Finite element simulation of the manufacturing process chain of a sheet metal assembly | |
| Deng et al. | Investigating the influence of external restraint on welding distortion in thin-plate bead-on joint by means of numerical simulation and experiment | |
| CN103246774B (en) | The method of numerical simulation P92 steel-pipe welding heat-affected zone width | |
| CN113673030B (en) | Simulation analysis method for ductile fracture coupling failure of metal material | |
| Ferro et al. | Quantification of the influence of residual stresses on fatigue strength of Al-alloy welded joints by means of the local strain energy density approach | |
| CN116227087A (en) | Method for predicting tensile characteristics of welded joint of thin-wall part based on finite element method | |
| CN111339703A (en) | Virtual prediction method for material hardening behavior under large strain condition | |
| CN111745276B (en) | Rapid simulation method for resistance spot welding residual stress and deformation of complex sheet metal component | |
| Wang et al. | Comparison of FE models to predict the welding distortion in T-joint gas metal arc welding process | |
| CN105740551A (en) | Weld joint fatigue life prediction method | |
| Arunkumar | Small punch creep test: an overview | |
| Mikihito et al. | A simplified FE simulation method with shell element for welding deformation and residual stress generated by multi-pass butt welding | |
| Deshpande et al. | Finite-element-based parametric study on welding-induced distortion of TIG-welded stainless steel 304 sheets | |
| Li et al. | Identification of material parameters from punch stretch test | |
| Saravanan et al. | Study on effects of spring back on sheet metal bending using simulation methods | |
| Adib et al. | Three-dimensional finite element analysis of tensile-shear spot-welded joints in tensile and compressive loading conditions | |
| CN114943121B (en) | Friction group welding additive part creep incubation period prediction method introducing residual stress | |
| Chang et al. | Analysis of residual stress in stainless steel pipe weld subject to mechanical axial tension loading | |
| Mahur et al. | Review on finite element analysis for estimation of residual stresses in welded structures | |
| Fan et al. | Multi-objective optimization of crimping of large-diameter welding pipe | |
| Pasupuleti et al. | Predictive Modelling and Process Parameter Prediction for Monel 400 Wire Electrical Discharge Machining for Rocket Frames | |
| Hyde et al. | A simplified method for predicting the creep crack growth in P91 welds at 650 C | |
| Adak et al. | Thermomechanical analysis through a pseudolinear equivalent constant stiffness system | |
| Beloufa | A Comprehensive Study on Optimizing Mechanical Stress, Contact Temperature, and Electrical Contact Resistance | |
| CN111141604A (en) | Prediction method for mechanical property of resistance spot-welded joint |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |